TheyÕre handing us an engine, transmission, breaks, and chassis and asking us to build a fast, safe, and reliable car,Ó a data scientist at a recently IPOÕed tech company opined, while describing the challenges he faces in delivering ML applications using existing tools and platforms. Although hundreds of new MLOps products have emerged in the past few years, data scientists and ML engineers are still struggling to develop, deploy, and maintain models and systems. In fact, iteration speeds for ML teams may be slowing! In this talk, Sarah Catanzaro, a General Partner at Amplify Partners, will discuss a dominant design for the ML stack, consider why this design inhibits effective model lifecycle management, and identify opportunities to resolve the key challenges that ML practitioners face.
